Hornbeck, HaysnAlim, Usman2021-06-152021-06-152019-10Hornbeck, H., & Alim, U. (2019). UofC-Bayes: A Bayesian approach to visualizing uncertainty in Likert Scales. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST). doi:10.1109/vast47406.2019.8986935http://hdl.handle.net/1880/113496https://doi.org/10.11575/PRISM/46121Disasters demand a quick response based on incomplete information. For the Saint Himark dataset, part of the 2019 VAST Challenge, we focused on delivering a visualization which accurately conveyed that uncertainty. While our analysis was done offline, we chose techniques and algorithms which could easily be applied to realtime usage. Our visualization for the first mini-challenge was a one-screen dashboard that summarized citizen feedback.© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.conference posterRGPIN-2019-05303http://dx.doi.org/10.1109/VAST47406.2019.8986935